Cargando…
Homomorphic inference of deep neural networks for zero-knowledge verification of nuclear warheads
Disarmament treaties have been the driving force towards reducing the large nuclear stockpile assembled during the Cold War. Further efforts are built around verification protocols capable of authenticating nuclear warheads while preventing the disclosure of confidential information. This type of pr...
Autores principales: | Turturica, Gabriel V., Iancu, Violeta |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10167340/ https://www.ncbi.nlm.nih.gov/pubmed/37156993 http://dx.doi.org/10.1038/s41598-023-34679-7 |
Ejemplares similares
-
A physical zero-knowledge object-comparison system for nuclear warhead verification
por: Philippe, Sébastien, et al.
Publicado: (2016) -
A physically cryptographic warhead verification system using neutron induced nuclear resonances
por: Engel, Ezra M., et al.
Publicado: (2019) -
Applying Deep Neural Networks over Homomorphic Encrypted Medical Data
por: Vizitiu, Anamaria, et al.
Publicado: (2020) -
Secure tumor classification by shallow neural network using homomorphic encryption
por: Hong, Seungwan, et al.
Publicado: (2022) -
Secure Inference on Homomorphically Encrypted Genotype Data with Encrypted Linear Models
por: Zou, Meng, et al.
Publicado: (2023)